Triple
T6301586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | François Mauriac |
E141266
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Le Figaro |
E349219
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Le Figaro | Statement: [François Mauriac, employer, Le Figaro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Figaro Context triple: [François Mauriac, employer, Le Figaro]
-
A.
Le Figaro
chosen
Le Figaro is one of France’s oldest and most influential daily newspapers, known for its conservative editorial stance and major role in the country’s cultural and political life.
-
B.
La Presse
La Presse is a prominent French-language newspaper historically known for serializing major literary works and influencing public opinion in France.
-
C.
Le Monde
Le Monde is a leading French daily newspaper known for its in-depth political, cultural, and international reporting.
-
D.
Le Moniteur universel
Le Moniteur universel was a prominent French newspaper and official government gazette that played a key role in disseminating political and cultural information from the late 18th to the 19th century.
-
E.
L’Express
L’Express is a major French weekly news magazine known for its political and intellectual commentary.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645bb41481909294b06e2b3e1845 |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e436e7ec8190a5ea470eb83ddaea |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:27 p.m.